In survival analysis, it often happens that some individuals, referred to as cured individuals, never experience the event of interest. When analyzing time-to-event data with a cure fraction, it is crucial to check the assumption of `sufficient follow-up', which means that the right extreme of the censoring time distribution is larger than that of the survival time distribution for the non-cured individuals. However, the available methods to test this assumption are limited in the literature. In this article, we study the problem of testing whether follow-up is sufficient for light-tailed distributions and develop a simple novel test. The proposed test statistic compares an estimator of the non-cure proportion under sufficient follow-up to one without the assumption of sufficient follow-up. A bootstrap procedure is employed to approximate the critical values of the test. We also carry out extensive simulations to evaluate the finite sample performance of the test and illustrate the practical use with applications to leukemia and breast cancer datasets.

翻译：在生存分析中，常存在部分个体（称为治愈个体）始终未发生感兴趣事件。在分析含治愈比例的时间-事件数据时，需验证"充分随访"这一关键假设，即删失时间分布的右尾部需超越非治愈个体的生存时间分布右尾部。然而文献中检验该假设的可用方法有限。本文针对轻尾分布研究充分随访性检验问题，提出一种简洁的新检验方法。所提出检验统计量比较了充分随访假设下与非充分随访假设下的未治愈比例估计值，并采用自助法近似检验临界值。通过大规模模拟实验评估该检验在有限样本下的表现，并应用于白血病和乳腺癌数据集以阐明其实用价值。